Senior Applied Machine Learning Engineer, Typographic Intelligence

Adobe Media and Data Science Research (MDSR) Laboratory

Base: $190,200 - $345,650 annually; california bas...
Hybrid
5-8 years production ml experience
Python programming proficiency
Pytorch or tensorflow framework expertise
This role focuses on applying advanced modeling to design, train, and operationalize ML systems for typographic layout and generative styling across Adobe's creative products

Job Summary

  • This role focuses on applying advanced modeling to design, train, and operationalize ML systems for typographic layout and generative styling across Adobe's creative products.
  • Candidates will own the entire modeling lifecycle from data preparation and training pipelines to production deployment, monitoring, and integration into hybrid product architectures.
  • The position requires strong software engineering fundamentals including writing production-quality code, tests, and automation while following CI/CD best practices.

Matching Summary

This role focuses on applying advanced modeling to design, train, and operationalize ML systems for typographic layout and generative styling across Adobe's creative products.

Salary

Base: $190,200 - $345,650 annually; California Base: $238,700 - $345,650; Short-term incentives in form of Annual Incentive Plan (AIP) and potential equity awards

Skills & Requirements

Must-have

  • 5-8 years production ML experience
  • Python programming proficiency
  • PyTorch or TensorFlow framework expertise
  • End-to-end model lifecycle ownership
  • Data pipeline and model serving infrastructure
  • CI/CD and software engineering best practices

Nice-to-have

  • Experience with diffusion models and GANs
  • Computer vision segmentation skills
  • Model optimization via quantization and distillation
  • Reinforcement learning or bandit methods
  • Background in recommendation systems or NLP
  • MS or PhD in Computer Science or ML

Key Requirements

  • 5-8 years building and operating production ML systems
  • Strong Python skills with PyTorch or TensorFlow
  • Demonstrated ownership of data to monitoring lifecycle
  • Experience debugging models and tuning hyperparameters
  • MS or PhD in Computer Science, ML, or related field (Nice to Have)

Work Rights

Not specified

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